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I gave a talk at GDC 2014 all about game analytics and AWS. In the talk, I showed how to start
small by uploading analytics files from users devices to S3, and then processing them with
Redshift. As your game grows, add more data sources and AWS services such as Kinesis
and Elastic MapReduce to perform more complex processing.
Here are the slides on Slideshare
and the videos on YouTube.

Linux distributions still ship with the assumption that they will be multi-user systems,
meaning resource limits are set for a normal human doing day-to-day desktop work. For a
high-performance system trying to serve thousands of concurrent network clients, these
limits are far too low. If you have an online game or web app that’s pushing the envelope,
these settings can help increase awesomeness.

more than I forsaw. Seems atomicity is a hot topic in the web world these days.
Increasing user concurrency, coupled with more interactive apps, exposes all sorts of edge cases.
I wanted to write a follow-up post to step back and look at a few more high-level concerns with
atomicity, as well as some Redis-specific issues we’ve seen.

You are probably not handling atomic operations properly in your app, and probably have some
nasty lurking race conditions. The worst part is these will get worse as your user count
increases, are difficult to reproduce, and usually happen in your most critical pieces of code.
(And no, your unit tests can’t catch them either.)